All Research Groups

The following research groups exist in the Computer Science Department. Applicants to the graduate program should apply to one of the groups listed below. They should indicate their choice on the admission application where it asks for "Intended area of research or specialization." Graduate applicants should
also check the faculty page to
see which faculty are on sabbatical or not accepting new graduate students.

The Center for Social and Cognitive Networks links together top social scientists, neuroscientists, and cognitive scientists with leading physicists, computer scientists, mathematicians, and engineers in the search to uncover, model, understand, and foresee the complex social interactions that take place in today's society. All aspects of social networks, from the origins of adversarial networks to gauging the level of trust within vast social networks, are investigated within the center.

This research focuses on the emerging area of Web Science and the evolving
web and related semantic technologies. Active areas of research include:
knowledge provenance and explanation; privacy, policy, and workflow
transparency; trust, social networking, and collaboration technologies;
cyberinfrastucture for data integration, particularly for science data;
ontology evolution environments; and ethical, policy, and social aspects of
Web use and usability.

Theory of Computation provides the foundation needed for effective
applications. The theory group at Rensselaer's Computer Science Department
brings together researchers in many areas of Computer Science to develop
novel approaches and solutions to problems in information technology.
Our research is characterized by close collaboration with researchers
in diverse application areas, such as networking; bioinformatics;
visualization; pattern recognition, physics and astronomy; digital library,
data mining; and experimental algorithmics.

Research in computer vision in the Department of Computer Science has
taken a new direction. Professor Charles Stewart and his students, both
graduate and undergraduate, are working on applications of computer
vision to problems in environmental monitoring, with the largest domain
being oceanography. A wide range of problems arise, including
illumination modeling and color correction, registration and 3d
reconstruction, motion analysis, and recognition. Practical issues
of high-volume throughput and large-scale software system development
are also under consideration.

In order for robots to reach their full potential as productive
members of society, they must become more autonomous, socially adept,
and dexterous. Toward this end, the research in the Computer Science
Robotics Laboratory is focused on three areas: grasping and
manipulation, physical simulation, and planning and control for
autonomous operation in unstructured environments.

The faculty and students in the Computer Graphics Research Group are
interested in a wide variety of rendering, geometry, simulation, and
visualization problems motivated by computer games, special effects in
movies, architectural design & pre-visualization, and many other
exciting applications. We study topics including physically-based
digital sculpting, efficient high-quality photo-realistic rendering,
new data representations and algorithms, and the use of modern
graphics hardware for interactive applications. Other topics include modeling terrain and compressing large datasets in
computational cartography and geographic information science.

Bioinformatics is the science of managing, retrieving, analyzing, and interpreting biological data. Research is being carried out on topics such as sequence assembly, protein and RNA structure prediction, sequence/structure/motifs, comparative genomics, and the gene regulatory networks. Research also spans emerging areas like microarray data analysis, protein design, high dimensional indexing,
database support, information integration, and data mining.

Researchers investigate computer networks and their
protocols, with a focus on wireless and sensor networks through
the International Technology Alliance, a new 10-year research consortium led
by the IBM Research Division and funded jointly by the US and UK Governments
with participation of the leading researchers in the world.
The focus is on sensor information processing and delivery, improvement
of the quality of information obtained from sensor networks and adaptation
of sensor networks to the dynamically changing user demands.
Another area of activity is the security of computers, networks, and sensors.
Secruity concerns are quickly becoming a significant barrier to the
wide-spread acceptance
of pervasive computing. The research tackles such issues as trust in
Internet communications, identity of groups on the Internet, cryptographic
and systemic challenges in sensor networks. Finally, in the area of
high-performance pervasive computing, the focus is on computational
environments in which task allocation, migration, and fault tolerance are
supported automatically and on application of such environments to
computations relevant to different scientific disciplines.

Researchers in the security group focus on security problems at the systems
level including discovering hidden networks in social networks;
network camouflaging; and privacy protection in data mining systems.

At the CogWorks Lab we are interested in basic and applied research in the
area of immediate interactive behavior. On the basic side, we are
working to understand the interplay of cognition, perception, and action
in routine interactive behavior. These interests entail understanding
top-down versus bottom-up control of behavior, the role of implicit versus
explicit knowledge, internal versus external representations, and knowledge
in-the-head versus knowledge in-the-world. On the applied side, we specialize
in the field of Cognitive Engineering (cognitive science theory applied to
human factors issues). Our research methods include behavioral and
performance measures (including eye-tracking), brain-based measures (EEG),
and computational cognitive modeling (usingACT-R, SanLab, and closed form
modeling).

Researchers in the RAIR Lab
design and build intelligent agents, software, robots, etc. on the basis
of formal logic. R&D has been and is sponsored by NSF, ARDA/DTO, AFOSR,
etc. PhD students need to have some background in logic, AI, and corresponding
programming paradigms.

The Programming Languages and Software Engineering research group
investigates programming models, languages, concepts, methodologies, and
tools to enable the development of correct, efficient, reliable, and
maintainable software.

This research area deals with the efficient and effective methods for
storing, querying and maintaining data from possibly disparate and
heterogeneous resources. Data is used in many different applications from
scientific data sets, sensor data, images, video and audio to hypertext
documents, and data on stock market behavior. Research focuses on methods for
caching data, querying large and distributed databases and supporting
applications such as computer-aided design and manufacturing and collaborative
engineering.

Current research in computational geometry has two themes. The first concentrates on algorithms for the reconstruction of smooth geometric objects from their samples. Problems of interest include characterizing the conditions on sampling density, which allow a curve to be reconstructed from its samples. The reconstruction is homeomorphic and sufficiently close to the original and the algorithms developed to achieve the reconstruction. Also involved are the dependence of such algorithms on the dimension of the embedding space, related algorithms for the reconstruction of surfaces and manifolds, and finding the most concise representation of a manifold in terms of its samples. A second research track focuses on applications of computational geometry, particularly in robotic motion planning.
The second computational geometry theme emphasizes small, simple, and
fast geometric data structures and algorithms. Note that efficiency in
both space and time can become more important as machines get
faster. This research is applicable to computational cartography,
computer graphics, computational geometry, and geographic information
science. GeoStar, a recently concluded DARPA-funded project in this
theme, modelled terrain to compress it and to site observers and then
to plot motion paths to avoid those observers. A current NSF-funded
project is modeling how levees erode as floodwaters overtop them.